Neural Nanotechnology: Nanowire Networks Learn And Remember Like A Human Brain

Artificial Intelligence Neural Network Concept Art

Scientists have demonstrated that nanowire networks can exhibit short- and long-term memory, similar to the human brain. These networks, comprised of highly conductive silver wires covered in plastic and arranged in a mesh-like pattern, mimic the physical structure of the human brain. The team successfully tested the nanowire network’s memory capabilities using a task similar to human psychology experiments. This breakthrough in nanotechnology suggests that non-biological hardware systems could potentially replicate brain-like learning and memory, and has numerous real-world applications, such as improving robotics and sensor devices in unpredictable environments.

Human-Like Intelligence Could Be Physical

In a groundbreaking study, an international team has shown that nanowire networks can mimic the short- and long-term memory functions of the human brain. This breakthrough paves the way for replicating brain-like learning and memory in non-biological systems, with potential applications in robotics and sensor devices.

An international team led by scientists at the University of Sydney has demonstrated nanowire networks can exhibit both short- and long-term memory like the human brain.

The research has been published today in the journal

Photograph of nanowire network (left), network’s pathways changing and strengthening (right). Credit: Alon Loeffler

“This work builds on our previous research in which we showed how nanotechnology could be used to build a brain-inspired electrical device with neural network-like circuitry and

Neural network (left) nanowire network (right). Credit: Loeffler et al.

Nanowire networks are a type of nanotechnology typically made from tiny, highly conductive silver wires that are invisible to the naked eye, covered in a plastic material, which are scattered across each other like a mesh. The wires mimic aspects of the networked physical structure of a human brain.

Advances in nanowire networks could herald many real-world applications, such as improving robotics or sensor devices that need to make quick decisions in unpredictable environments.

“This nanowire network is like a synthetic neural network because the nanowires act like neurons, and the places where they connect with each other are analogous to synapses,” senior author Professor Zdenka Kuncic, from the School of Physics, said.

“Instead of implementing some kind of

Zdenka Kuncic. Credit: University of Sydney

To test the capabilities of the nanowire network, the researchers gave it a test similar to a common memory task used in human psychology experiments, called the N-Back task.

For a person, the N-Back task might involve remembering a specific picture of a cat from a series of feline images presented in a sequence. An N-Back score of 7, the average for people, indicates the person can recognize the same image that appeared seven steps back.

When applied to the nanowire network, the researchers found it could ‘remember’ a desired endpoint in an electric circuit seven steps back, meaning a score of 7 in an N-Back test.

“What we did here is manipulate the voltages of the end electrodes to force the pathways to change, rather than letting the network just do its own thing. We forced the pathways to go where we wanted them to go,” Dr. Loeffler said.